The Computational Design of Drug Sensors and Adsorbents for Environmental Applications

Molecularly Imprinted Polymers (MIPs) are synthetic receptors prepared via imprinting technology that can be tailored towards a specific analyte. The advantages of these "plastic antibodies" over their natural counterparts include low-cost, straightforward preparation and superior thermal and chemical stability. This method is versatile and can be used for detection and extraction of biomolecules ranging from ions to larger macrostructures such as bacteria. In the imprinting process, a complex between the template and suitable functional monomers is created and subsequently polymerized with cross-linker monomers to form a dense network. The key to obtaining high-affinity binding sites is the understanding of the nature of the "pre-polymerization complex". Computational modelling can elucidate the role of each molecular interaction that will feed into the design of the optimal MIP.

This PhD will develop and validate computational and experimental methodologies for a combined in-silico/in-vitro design framework for optimal MIPs aiming to the detection of drug molecules in water systems. Specifically, the selected case study is the antidepressant Fluoxetine (Prozac). Recent reports on environmental analysis suggest substantial contamination of water with this drug, which has a negative impact on aquatic life. Therefore, it is of significant interest to develop a portable sensor for the monitoring of Prozac concentrations on-site.

The candidate will perform the molecular modelling and subsequent experimental synthesis of an optimally designed Prozac-MIP sensor. The candidate has already demonstrated experimental competence in the field of MIP. The initial steps of this PhD will provide them with the required computational skills for the project, as further detailed in the training section.